Custom AI agent development — autonomous, tool-using systems
We engineer custom AI agents that reason, call your tools and take real actions — built on orchestration, function calling, memory, retrieval (RAG) and guardrails. As an AI agent development company in Kuala Lumpur, we design, build and integrate them for clients across Malaysia and worldwide.
Tool-using · model-neutral · guardrailed & observable.
The engineering that makes an AI agent actually work
Every custom AI agent we ship is built from the same core components — assembled and tuned for your workflow, your tools and your data.
Reasoning & orchestration
The control loop that lets an agent plan multi-step tasks, decide which tool to call next, and recover when a step fails.
Tool & function calling
Your systems exposed to the agent as typed, permission-scoped functions, so it can read data and take real actions through APIs.
Memory & retrieval (RAG)
Short- and long-term memory plus retrieval over a vector database, so the agent answers from your own knowledge, not guesses.
Guardrails & safety
Input/output validation, confidence thresholds, allow-lists and human-in-the-loop approval for anything risky or irreversible.
Multi-agent systems
Where one agent isn’t enough, a planner-and-workers pattern — specialised agents that hand off tasks and coordinate on a goal.
Evaluation & observability
Tracing, eval sets and logging of every tool call and decision, so you can measure accuracy and debug what the agent did.
We build on frontier models — Claude, OpenAI and Gemini — with LangChain-style orchestration, function calling and vector databases for RAG, then connect the agent to your tools through n8n, Make, Zapier and direct APIs.
A disciplined build process, from scope to a live agent
An engineering pipeline that turns a use case into a tested, integrated and observable AI agent in production.
The kinds of AI agents we build
Customer Support Agent
Resolves tickets end to end — retrieves order and account data, drafts replies and escalates edge cases to a human.
Sales & Research Agent
Enriches leads, researches accounts across the web and your CRM, and prepares briefs before a rep ever picks up.
Internal Knowledge Agent
An agent over your Notion, Drive and wikis that answers staff questions with citations and keeps humans out of search.
Operations Agent
Watches queues and triggers, then routes, updates records and orchestrates multi-step workflows across your tools.
Transparent scoping, fixed quotes
We don’t sell open-ended retainers. After a free scoping call we quote a fixed price before any build begins. A few technical factors drive that scope:
Agents engineered to run in production
Real tool use, not demos
We build agents that take actions in your live systems — not chat wrappers that only return text.
Model-neutral engineering
Claude, OpenAI or Gemini — we pick the model per task on accuracy, latency, cost and data-sensitivity.
Guardrails by default
Validation, allow-lists and human approval on risky actions are built in, not bolted on later.
Grounded in your data
RAG over your own knowledge keeps answers factual and traceable instead of confidently wrong.
Observable & ownable
Every run is logged and evaluated, and you own the code, prompts and configuration we hand over.
KL-based, globally minded
On the ground in Kuala Lumpur, building and deploying agents for clients across Malaysia and worldwide.
Where AI agents fit next
AI agent development questions
What is an AI agent, and how is it different from a chatbot?
A chatbot answers; an agent acts. A custom AI agent reasons over a goal, calls tools and APIs through function calling, reads and updates your systems, remembers context across steps, and can chain several actions to complete a task — with guardrails and, where needed, a human approval step. A chatbot mostly returns text; an agent orchestrates real work end to end.
What can a custom AI agent connect to and take actions in?
Anything with an API or a permissioned automation layer. We wire agents into CRMs like HubSpot, workspaces like Notion, Slack and Google Drive, databases and spreadsheets like Airtable, and orchestration platforms like n8n, Make and Zapier. Each tool is exposed to the agent as a typed function with scoped permissions, so it can only do what you allow.
How do you keep an AI agent accurate and stop it taking wrong actions?
Several layers. We ground answers in your own data with retrieval (RAG) over a vector database so the agent works from facts, not guesses; we constrain it to typed tools with validation; we add guardrails, confidence thresholds and fallbacks; and we keep risky or irreversible actions behind human-in-the-loop approval. Every run is logged so you can trace exactly what the agent did and why.
What technologies and models do you build AI agents with?
We are model-neutral. We build on frontier LLMs such as Claude, OpenAI’s models and Gemini, with LangChain-style orchestration, function/tool calling, and vector databases for RAG. For tool execution and workflow glue we use n8n, Make or Zapier and direct API integrations. We pick the model and stack that fit your accuracy, latency, cost and data-sensitivity needs.
How long does it take to build a custom AI agent?
A single-purpose agent with a couple of integrations is typically a few weeks from scope to a working, tested deployment. Multi-agent systems, many tool connections, or strict compliance requirements take longer. We scope the timeline precisely after a free discovery call and usually ship a narrow first agent before expanding.
Do we own the agent, its code and prompts after handover?
Yes. You own the agent, its orchestration code, prompts, tool definitions and configuration, and it runs in your accounts and infrastructure wherever possible. We hand over documentation so your team — or another vendor — can run, extend or migrate it without being locked to us.
How do you handle data privacy and security for AI agents?
We minimise the data each agent touches, scope every tool with least-privilege permissions, and keep secrets and API keys out of prompts. Sensitive or irreversible actions stay under human approval, all tool calls are logged, and we can architect hosted, bring-your-own-key or private/on-device model setups depending on how sensitive your data is.
Who maintains and monitors the agent once it is live?
We instrument every agent with logging, evaluation and error alerting so failures and drift are caught early. After launch you can run it yourself with our documentation, or we can provide ongoing monitoring, prompt and tool tuning, and model upgrades as the underlying models improve — your choice, not a locked-in retainer.
Will an AI agent replace our team?
No. Agents remove repetitive, multi-step busywork — triage, lookups, data entry, routing, first-draft work — so your people spend time on judgement, relationships and exceptions. We design agents to augment your team with a human in the loop for anything sensitive, not to run your business unsupervised.
Do you work with businesses outside Malaysia?
Yes. We are based in Kuala Lumpur and build and deploy AI agents for clients across Malaysia and internationally, working remotely.